We shared this request example with FAB participants: url_qparams = { "limit": count, "offset": offset, "has_group": "false", "order_by": "-activity", "forecast_type": "binary", "project": tournament_id, "status": "open", "type": "forecast", "include_description": "true", } url = f"{api_info.base_url}/questions/" response = requests.get( url, headers={"Authorization": f"Token {api_info.token}"}, params=url_qparams )

But we don't want to support all these parameters, and the ones relevant are: - order_by - status - project - forecast_type - we ignore this, but assume it's binary - FAB only supports binary for now.

GET /api2/questions/?format=api&offset=480
HTTP 200 OK
Allow: GET, OPTIONS
Content-Type: application/json
Vary: Accept

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            "short_title": "Will the US pass \"no tax on tips\"?",
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                "description": "The federal budget process in the United States begins with the passage of a [<u>budget resolution</u>](https://www.cbpp.org/research/introduction-to-budget-reconciliation#how-does-congress-start-the-cbpp-anchor) — a concurrent resolution passed by both the House and Senate that sets broad fiscal targets for spending, revenue, the deficit, and debt levels. While it provides a framework for the upcoming fiscal year, it does not become law and does not require the president's signature. Importantly, the budget resolution may include reconciliation instructions, which direct specific congressional committees to draft legislation that meets the resolution's fiscal goals. These instructions are optional but allow for the creation of a [<u>reconciliation bill</u>](https://www.cbpp.org/research/introduction-to-budget-reconciliation), which allows the Senate to pass certain budget-related laws with a simple majority vote and limited debate, bypassing the [<u>filibuster</u>](https://www.senate.gov/about/powers-procedures/filibusters-cloture.htm).\n\nIf reconciliation instructions are included, the resulting reconciliation bill must be passed by both chambers and signed by the president to become law. It can include changes to spending, revenue, or the debt limit, but is restricted by rules such as the [<u>Byrd Rule</u>](https://www.cbpp.org/research/introduction-to-budget-reconciliation#what-is-the-byrd-rule-cbpp-anchor), which prohibits provisions unrelated to budget changes. If the budget resolution does not include reconciliation instructions, Congress must enact any fiscal changes through the regular legislative process. In this case, changes to [<u>discretionary spending</u>](https://fiscaldata.treasury.gov/americas-finance-guide/federal-spending/#the-difference-between-mandatory-discretionary-and-supplemental-spending) are made through the annual appropriations bills, which fund specific government departments and require presidential approval. Changes to mandatory spending programs (like Medicare, [<u>Medicaid</u>](https://usafacts.org/articles/how-much-of-the-federal-budget-is-mandatory-spending/), or Social Security), however, require standalone legislation that amends the law governing those programs. These also must pass both chambers and be signed by the president, and they generally face a higher procedural hurdle in the Senate due to the possibility of a filibuster.\n\nDuring his 2024 campaign, President Trump [<u>promised to eliminate taxes on tips</u>](https://www.washingtonpost.com/politics/2024/06/09/trump-tipped-wage-tax-cut/) for service workers, a proposal that resonated with restaurant and hospitality workers. Critics argue that the benefit would [<u>help very few Americans</u>](https://taxpolicycenter.org/taxvox/exempting-tips-federal-income-tax-would-benefit-very-few-workers) and not target benefits to low-income workers, while [<u>supporters</u>](https://www.cnn.com/2024/08/12/politics/taxes-on-tips-eliminate-proposal-harris) contend it would provide tax relief to millions of hardworking Americans in the service industry.\n\nOn May 14, 2025, the [<u>House Ways and Means Committee marked up</u>](https://waysandmeans.house.gov/wp-content/uploads/2025/05/The-One-Big-Beautiful-Bill-Section-by-Section.pdf) its proposed section of the reconciliation bill. This legislation allows taxpayers to deduct \"qualified tips\" received in the course of working in an occupation \"which traditionally and customarily receives tips.\"",
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            "description": "The federal budget process in the United States begins with the passage of a [<u>budget resolution</u>](https://www.cbpp.org/research/introduction-to-budget-reconciliation#how-does-congress-start-the-cbpp-anchor) — a concurrent resolution passed by both the House and Senate that sets broad fiscal targets for spending, revenue, the deficit, and debt levels. While it provides a framework for the upcoming fiscal year, it does not become law and does not require the president's signature. Importantly, the budget resolution may include reconciliation instructions, which direct specific congressional committees to draft legislation that meets the resolution's fiscal goals. These instructions are optional but allow for the creation of a [<u>reconciliation bill</u>](https://www.cbpp.org/research/introduction-to-budget-reconciliation), which allows the Senate to pass certain budget-related laws with a simple majority vote and limited debate, bypassing the [<u>filibuster</u>](https://www.senate.gov/about/powers-procedures/filibusters-cloture.htm).\n\nIf reconciliation instructions are included, the resulting reconciliation bill must be passed by both chambers and signed by the president to become law. It can include changes to spending, revenue, or the debt limit, but is restricted by rules such as the [<u>Byrd Rule</u>](https://www.cbpp.org/research/introduction-to-budget-reconciliation#what-is-the-byrd-rule-cbpp-anchor), which prohibits provisions unrelated to budget changes. If the budget resolution does not include reconciliation instructions, Congress must enact any fiscal changes through the regular legislative process. In this case, changes to [<u>discretionary spending</u>](https://fiscaldata.treasury.gov/americas-finance-guide/federal-spending/#the-difference-between-mandatory-discretionary-and-supplemental-spending) are made through the annual appropriations bills, which fund specific government departments and require presidential approval. Changes to mandatory spending programs (like Medicare, [<u>Medicaid</u>](https://usafacts.org/articles/how-much-of-the-federal-budget-is-mandatory-spending/), or Social Security), however, require standalone legislation that amends the law governing those programs. These also must pass both chambers and be signed by the president, and they generally face a higher procedural hurdle in the Senate due to the possibility of a filibuster.\n\nDuring his 2024 campaign, President Trump [<u>promised to eliminate taxes on tips</u>](https://www.washingtonpost.com/politics/2024/06/09/trump-tipped-wage-tax-cut/) for service workers, a proposal that resonated with restaurant and hospitality workers. Critics argue that the benefit would [<u>help very few Americans</u>](https://taxpolicycenter.org/taxvox/exempting-tips-federal-income-tax-would-benefit-very-few-workers) and not target benefits to low-income workers, while [<u>supporters</u>](https://www.cnn.com/2024/08/12/politics/taxes-on-tips-eliminate-proposal-harris) contend it would provide tax relief to millions of hardworking Americans in the service industry.\n\nOn May 14, 2025, the [<u>House Ways and Means Committee marked up</u>](https://waysandmeans.house.gov/wp-content/uploads/2025/05/The-One-Big-Beautiful-Bill-Section-by-Section.pdf) its proposed section of the reconciliation bill. This legislation allows taxpayers to deduct \"qualified tips\" received in the course of working in an occupation \"which traditionally and customarily receives tips.\""
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                "description": "A survey released in 2024 [found](https://www.bestcolleges.com/research/students-worry-about-ai-impacts-survey/) that 53% of college students agreed with the statement, \"I am worried about the impacts of AI on the workforce in general.\" Additionally, 37% were worried about the impact of AI on their own desired career path, with a full 27% even saying they were doubting or reconsidering their majors due to AI. In STEM subjects, the issue is even more pronounced, with 1 in 3 STEM majors doubting or reconsidering their major.\n\nA 2024 survey of hiring managers [found](https://www.intelligent.com/8-in-10-companies-plan-to-layoff-recent-college-grads-this-year-due-to-ai/) that 78% saying that recent college graduates would be laid off because of AI and 69% fully or somewhat agreeing with the statement that AI can do the word of a recent graduate. Among the tasks most cited as being able to be offloaded to AI were email writing (by 73% of respondents), data entry (73%), research (63%), and customer support (61%).\n\nAt the time of this question, an inordinate surge in unemployment of college graduates is not yet apparent in the data, at least in the 20-24 age range:\n<iframe src=\"https://fred.stlouisfed.org/graph/graph-landing.php?g=1J7Hc&amp;width=670&amp;height=475\" scrolling=\"no\" frameborder=\"0\" style=\"overflow:hidden; width:670px; height:525px;\" loading=\"lazy\"></iframe> &nbsp;\nHowever, a recent Atlantic article [Something Alarming Is Happening to the Job Market](https://www.aol.com/sign-ai-competing-college-grads-100000034.html) by Derek Thompson discussed a recent deterioration in job conditions for recent college graduates, with reports of MBA students having trouble finding work, as well as a surge in law school applications, which can be a sign of some students perceiving a poor job market.  One theory is an economy that has not fully recovered from the coronavirus pandemic, which caused a massive surge in unemployment of recent grads and saw white collar jobs hardest hit. Another theory is that the lifetime earnings gap between college and non-college careers peaked in 2010 and that therefore the investment return from a college degree is less certain than it used to be.\n\nA third theory is AI. According to Thompson:\n\n> Consider, then, a novel economic indicator: the recent-grad gap. It’s the difference between the unemployment of young college graduates and the overall labor force. Going back four decades, young college graduates almost always have a lower—sometimes much lower—unemployment rate than the overall economy, because they are relatively cheap labor and have just spent four years marinating in a (theoretically) enriching environment.\n\n> But last month’s recent-grad gap hit an all-time low. That is, today’s college graduates are entering an economy that is relatively worse for young college grads than any month on record, going back at least four decades.\n\n> The strong interpretation of this graph is that it’s exactly what one would expect to see if firms replaced young workers with machines. As law firms leaned on AI for more paralegal work, and consulting firms realized that five 22-year-olds with ChatGPT could do the work of 20 recent grads, and tech firms turned over their software programming to a handful of superstars working with AI co-pilots, the entry level of America’s white-collar economy would contract.\n\nFor more information, see:\n\n* BLS: [Incorporating AI impacts in BLS employment projections: occupational case studies](https://www.bls.gov/opub/mlr/2025/article/incorporating-ai-impacts-in-bls-employment-projections.htm)\n* Infinitive: [The Looming Impact of AI on U.S. Jobs](https://infinitive.com/the-looming-impact-of-ai-on-us-jobs/)\n* Nexford U: [How Will Artificial Intelligence Affect Jobs 2024-2030](https://www.nexford.edu/insights/how-will-ai-affect-jobs)\n* Understanding AI: [Why I'm not worried about AI causing mass unemployment](https://www.understandingai.org/p/software-didnt-eat-the-world)",
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            "description": "A survey released in 2024 [found](https://www.bestcolleges.com/research/students-worry-about-ai-impacts-survey/) that 53% of college students agreed with the statement, \"I am worried about the impacts of AI on the workforce in general.\" Additionally, 37% were worried about the impact of AI on their own desired career path, with a full 27% even saying they were doubting or reconsidering their majors due to AI. In STEM subjects, the issue is even more pronounced, with 1 in 3 STEM majors doubting or reconsidering their major.\n\nA 2024 survey of hiring managers [found](https://www.intelligent.com/8-in-10-companies-plan-to-layoff-recent-college-grads-this-year-due-to-ai/) that 78% saying that recent college graduates would be laid off because of AI and 69% fully or somewhat agreeing with the statement that AI can do the word of a recent graduate. Among the tasks most cited as being able to be offloaded to AI were email writing (by 73% of respondents), data entry (73%), research (63%), and customer support (61%).\n\nAt the time of this question, an inordinate surge in unemployment of college graduates is not yet apparent in the data, at least in the 20-24 age range:\n<iframe src=\"https://fred.stlouisfed.org/graph/graph-landing.php?g=1J7Hc&amp;width=670&amp;height=475\" scrolling=\"no\" frameborder=\"0\" style=\"overflow:hidden; width:670px; height:525px;\" loading=\"lazy\"></iframe> &nbsp;\nHowever, a recent Atlantic article [Something Alarming Is Happening to the Job Market](https://www.aol.com/sign-ai-competing-college-grads-100000034.html) by Derek Thompson discussed a recent deterioration in job conditions for recent college graduates, with reports of MBA students having trouble finding work, as well as a surge in law school applications, which can be a sign of some students perceiving a poor job market.  One theory is an economy that has not fully recovered from the coronavirus pandemic, which caused a massive surge in unemployment of recent grads and saw white collar jobs hardest hit. Another theory is that the lifetime earnings gap between college and non-college careers peaked in 2010 and that therefore the investment return from a college degree is less certain than it used to be.\n\nA third theory is AI. According to Thompson:\n\n> Consider, then, a novel economic indicator: the recent-grad gap. It’s the difference between the unemployment of young college graduates and the overall labor force. Going back four decades, young college graduates almost always have a lower—sometimes much lower—unemployment rate than the overall economy, because they are relatively cheap labor and have just spent four years marinating in a (theoretically) enriching environment.\n\n> But last month’s recent-grad gap hit an all-time low. That is, today’s college graduates are entering an economy that is relatively worse for young college grads than any month on record, going back at least four decades.\n\n> The strong interpretation of this graph is that it’s exactly what one would expect to see if firms replaced young workers with machines. As law firms leaned on AI for more paralegal work, and consulting firms realized that five 22-year-olds with ChatGPT could do the work of 20 recent grads, and tech firms turned over their software programming to a handful of superstars working with AI co-pilots, the entry level of America’s white-collar economy would contract.\n\nFor more information, see:\n\n* BLS: [Incorporating AI impacts in BLS employment projections: occupational case studies](https://www.bls.gov/opub/mlr/2025/article/incorporating-ai-impacts-in-bls-employment-projections.htm)\n* Infinitive: [The Looming Impact of AI on U.S. Jobs](https://infinitive.com/the-looming-impact-of-ai-on-us-jobs/)\n* Nexford U: [How Will Artificial Intelligence Affect Jobs 2024-2030](https://www.nexford.edu/insights/how-will-ai-affect-jobs)\n* Understanding AI: [Why I'm not worried about AI causing mass unemployment](https://www.understandingai.org/p/software-didnt-eat-the-world)"
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                "description": "[According to Crowdstrike](https://www.crowdstrike.com/en-us/cybersecurity-101/artificial-intelligence/agentic-ai/):\n\n> Artificial intelligence has come a long way from rule-based systems that simply follow instructions. Now, with agentic AI, we’re entering the era where AI actively makes decisions, learns from its environment and takes action without human intervention.\n\nHere are some of the examples listed by Crowdstrike:\n\n> Industrial robots: Agentic AI enables industrial robots to adapt in real time to drive efficiency improvements in manufacturing, logistics and customer interactions. In warehouses, AI-powered robotic systems dynamically adjust to shifting inventory demands, while in the retail and hospitality industries, robots equipped with agentic AI can provide personalized customer assistance.\n\n> Self-driving vehicles: Autonomous vehicles rely on agentic AI to process vast amounts of sensor data, predict the behavior of other drivers and make real-time navigation decisions. By continuously learning from road conditions and traffic patterns, self-driving systems improve safety and efficiency.&#x20;\n\n> AI-driven virtual assistants: Agentic AI-powered virtual assistants can anticipate user needs, prioritize tasks and autonomously handle scheduling conflicts. These assistants can analyze contextual information, such as work deadlines and personal preferences, to optimize daily productivity.\n\n> AI companions for customer support: Businesses are leveraging AI-driven chatbots and virtual agents that go beyond simple, scripted responses. These AI systems can engage in dynamic conversations, detect sentiment and provide intelligent recommendations.\n\nHowever, agentic AI also has risks, for example:\n\n> Safety and control: As AI systems become more autonomous, the real challenge is in keeping them aligned with human values and safety standards. Agentic AI must be designed to align with human intentions. Building fail-safes and oversight mechanisms into these systems is essential for maintaining control without stifling innovation.\n\nAdditional concerns have been raised about agentic AI possibly taking away jobs from humans, causing issues with data security, prevention of bias, and transparency on the part of the AI systems. ([Lexis-Nexis](https://www.lexisnexis.com/community/insights/legal/b/thought-leadership/posts/the-future-of-agentic-ai-navigating-ethical-and-societal-implications))&#x20;\n\nIn 2023, Italy temporarily banned ChatGPT, citing privacy concerns. ([Reuters](https://www.reuters.com/technology/italy-data-protection-agency-opens-chatgpt-probe-privacy-concerns-2023-03-31/#:~:text=MILAN%2FSTOCKHOLM%2C%20March%2031%20%28Reuters%29%20,suspected%20breach%20of%20privacy%20rules)) AI researcher Yoshua Bengio [has called for](https://yoshuabengio.org/2023/05/07/ai-scientists-safe-and-useful-ai/), as one option, policy banning the most powerful autonomous AI systems unless proven safe.  Others have made similar proposals.&#x20;\n\nThe European Union is in the process of implementing the [AI Act,](https://en.wikipedia.org/wiki/Artificial_Intelligence_Act) which passed in 2024. It offers a flexible approach to regulation based on perceived risk levels, with the highest levels of risk being assigned to AI used for manipulation, deception and exploitation of vulnerabilities. Other risk aspects regulators have been tasked with assessing are AI safety components whose failures could put human life at risk, as well as AI tools that could interfere with people's fundamental rights, such as if it were used by local law enforcement.  Recently the EU Commission formally [banned](https://techstrong.ai/agentic-ai/eu-closes-door-to-ai-agents-in-virtual-meetings/) AI agents from its meetings.&#x20;\n\nIn the United States, no specific legislation has been enacted, but Elon Musk, Steve Wozniak and other tech leaders in 2023 [signed a letter](https://www.nytimes.com/2023/03/29/technology/ai-artificial-intelligence-musk-risks.html) calling for a pause on the most advanced AI systems, citing safety concerns. In Canada, efforts [are being made](https://www.whitecase.com/insight-our-thinking/ai-watch-global-regulatory-tracker-canada) to expand AI regulation, especially regulation focused on protecting user privacy (but not necessarily agentic AI as yet).&#x20;\n\nSee also:\n\n* [AI Watch: Global regulatory tracker](https://www.whitecase.com/insight-our-thinking/ai-watch-global-regulatory-tracker#home)\n* [Agents Under Attack: Threat Modeling Agentic AI](https://www.cyberark.com/resources/threat-research-blog/agents-under-attack-threat-modeling-agentic-ai)",
                "resolution_criteria": "This question resolves as **Yes** if according to [credible reports](https://www.metaculus.com/faq/#definitions) a regulatory body with the authority to do so has announced a ban on the deployment of autonomous AI agents within the majority of the geographic area of any Organization for Economic Cooperation and Development (OECD) member country before January 1, 2030.",
                "fine_print": "The date a ban takes effect is immaterial. This question resolves to the date of an announcement and will resolve **Yes** as long as a ban is announced before January 1, 2030.\n\nAlthough this question anticipates the most likely path to a ban on deployment of autonomous AI agents would come about through executive action, if it came about through legislation then that would count as well, provided all the other criteria are met. Similarly, a ban that was not imposed directly on AI companies, but prevented the deployment of AI agents in a different way, e.g. by banning ISPs from giving access to them, would count.\n\nThe ban does not need to target AI agents specifically; any broader ban that encompasses all AI agents would resolve this question as **Yes**.\n\nSubsequent reversals of a ban will not cause the question to re-resolve.\n\nFor purposes of this question, an \"autonomous AI agent\" [is defined as](https://aws.amazon.com/what-is/ai-agents/):\n\n> a software program that can interact with its environment, collect data, and use the data to perform self-determined tasks to meet predetermined goals. Humans set goals, but an AI agent independently chooses the best actions it needs to perform to achieve those goals. For example, consider a contact center AI agent that wants to resolves \\[*sic*] customer queries. The agent will automatically ask the customer different questions, look up information in internal documents, and respond with a solution. Based on the customer responses, it determines if it can resolve the query itself or pass it on to a human.\n\nRegulations on behavior of autonomous AI agents, such as the prohibition on manipulative behavior in [Recital 29](https://artificialintelligenceact.eu/recital/29/) of the EU Artificial Intelligence Act, are not by themselves sufficient for a Yes resolution.&#x20;\n\nLimited or targeted bans, such as prohibitions on use by minors or by employees of government agencies, are not sufficient. In order to count, a ban must be for the general population.&#x20;\n\nIf there are exemptions from a general ban, such as allowing deployment by licensed university researchers or intelligence officers, it will still count.&#x20;\n\nOECD member states will be considered to be the following, regardless of the OECD's membership changes after the launch of this question: Australia, Austria, Belgium, Canada, Chile, Colombia, Costa Rica, the Czech Republic, Denmark, Estonia, Finland, France, Germany, Greece, Hungary, Iceland, Ireland, Israel, Italy, Japan, Latvia, Lithuania, Luxembourg, Mexico, the Netherlands, New Zealand, Norway, Poland, Portugal, Slovakia, Slovenia, South Korea, Spain, Sweden, Switzerland, Turkey, the United Kingdom and the United States.",
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